Prediction, detection and control of neurological events, as for example events in neurological disorders remain important medical concerns. Epilepsy is a common type of neurological disorder. Seizures and epilepsy have been recognized since antiquity, yet the medical community continues to struggle with defining and understanding these paroxysms of neuronal activity. Epileptic seizures are commonly considered to be the result of monolithic, hypersynchronous activity arising from unbalanced excitation-inhibition in large populations of cortical neurons (Penfield W G, Jasper H H. Epilepsy and the functional anatomy of the human brain. 1954 Boston: Little Brown; Schwartzkroin P A. Basic mechanisms of epileptogenesis. In E. Wyllie, editor, The treatment of Epilepsy. 1993 Philadelphia: Lea and Febiger, pp. 83-98; Fisher R S, et al. 2005 Epilepsia 46(4): 470-472). This view of ictal activity is highly simplified and the level at which it breaks down is unclear. It is largely based on electroencephalogram (EEG) recordings, which reflect the averaged activity of millions of neurons.
In animal models, sparse and asynchronous neuronal activity evolves, at seizure initiation, into a single hypersynchronous cluster with elevated spiking rates (Jiruska P, et al. 2010 J Neurosci 30(16): 5690-5701; Pinto D J, et al. 2005 J Neurosci 25(36): 8131-8140), as the canonical view would suggest. How well these animal models capture mechanisms operating in human epilepsy remains an open question (Jefferys J G R. 2003 Epilepsia 44(suppl. 12): 44-50; Buckmaster P S. 2004 Comp Medicine 54(5): 473-485). Very few human studies have gone beyond macroscopic scalp and intracranial EEG signals to examine neuronal spiking underlying seizures (Halgren E, et al. 1977 Epilepsia 18(1): 89-93; Wyler A R, et al. 1982 Ann Neurol 11: 301-308; Babb T L, et al. 1987 Electroencephalography Clin Neurophysiol 66: 467-482; Engel A K, et al. 2005 Nature Rev Neurosci 6: 35-47). The relationship between single neuron spiking and interictal discharges showed 1-2 single units recorded from two patients, and neuronal activity during the ictal state was not exathined (Wyler A R, et al. 1982 Ann Neurol 11: 301-308). A few recorded neurons tended to increase their spiking rates during epileptiform activity (Babb T L, et al. 1987 Electroencephalography Clin Neurophysiol 66: 467-482). However, these recordings were limited to the amygdala and hippocampal formation, not neocortex, and mostly auras and subclinical seizures. Hence the behavior of single neurons in human epilepsy remains largely unknown.
Single-neuron action potential (spiking) activity depends on intrinsic biophysical properties and the neuron's interactions in neuronal ensembles. In contrast with ex vivo/in vitro preparations, cortical pyramidal neurons in intact brain each commonly receive thousands of synaptic connections arising from a combination of short- and long-range axonal projections in highly recurrent networks (Braitenberg, V et al., Cortex: Statistics and Geometry of Neuronal Connectivity, Springer-Verlag, New York, 1998; Elston, G. N. et al., 2002 Cereb. Cortex 12, 1071-1078; Dayan, P. et al., Theoretical Neuroscience, MIT Press, Cambridge, Mass., 2001). Typically, a considerable fraction of these synaptic inputs is simultaneously active in behaving animals, resulting in ‘high-conductance’ membrane states (Destexhe, A. et al., 2003 Nat. Rev. Neurosci. 4, 739-751); that is, lower membrane input resistance and more depolarized membrane potentials. The large number of synaptic inputs and the associated high-conductance states contribute to the high stochasticity of spiking activity and the typically weak correlations observed among randomly sampled pairs of cortical neurons.